.. SPDX-License-Identifier: GPL-2.0 =====================================Using Propeller with the Linux kernel===================================== This enables Propeller build support for the kernel when using Clangcompiler. Propeller is a profile-guided optimization (PGO) method usedto optimize binary executables. Like AutoFDO, it utilizes hardwaresampling to gather information about the frequency of execution ofdifferent code paths within a binary. Unlike AutoFDO, this informationis then used right before linking phase to optimize (among others)block layout within and across functions. A few important notes about adopting Propeller optimization: #. Although it can be used as a standalone optimization step, it is   strongly recommended to apply Propeller on top of AutoFDO,   AutoFDO+ThinLTO or Instrument FDO. The rest of this document   assumes this paradigm. #. Propeller uses another round of profiling on top of   AutoFDO/AutoFDO+ThinLTO/iFDO. The whole build process involves   "build-afdo - train-afdo - build-propeller - train-propeller -   build-optimized". #. Propeller requires LLVM 19 release or later for Clang/Clang++   and the linker(ld.lld). #. In addition to LLVM toolchain, Propeller requires a profiling   conversion tool: https://github.com/google/llvm-propeller. Current supported architectures include x86/X86_64 (via LBR),and arm64 (via SPE). The Propeller optimization process involves the following steps: #. Initial building: Build the AutoFDO or AutoFDO+ThinLTO binary as   you would normally do, but with a set of compile-time / link-time   flags, so that a special metadata section is created within the   kernel binary. The special section is only intend to be used by the   profiling tool, it is not part of the runtime image, nor does it   change kernel run time text sections. #. Profiling: The above kernel is then run with a representative   workload to gather execution frequency data. This data is collected   using hardware sampling, via perf. Propeller is most effective on   platforms supporting advanced PMU features like LBR on Intel   machines. This step is the same as profiling the kernel for AutoFDO   (the exact perf parameters can be different). #. Propeller profile generation: Perf output file is converted to a   pair of Propeller profiles via an offline tool. #. Optimized build: Build the AutoFDO or AutoFDO+ThinLTO optimized   binary as you would normally do, but with a compile-time /   link-time flag to pick up the Propeller compile time and link time   profiles. This build step uses 3 profiles - the AutoFDO profile,   the Propeller compile-time profile and the Propeller link-time   profile. #. Deployment: The optimized kernel binary is deployed and used   in production environments, providing improved performance   and reduced latency. Preparation=========== Configure the kernel with::    CONFIG_AUTOFDO_CLANG=y   CONFIG_PROPELLER_CLANG=y Customization============= The default CONFIG_PROPELLER_CLANG setting covers kernel space objectsfor Propeller builds. One can, however, enable or disable Propeller buildfor individual files and directories by adding a line similar to thefollowing to the respective kernel Makefile: - For enabling a single file (e.g. foo.o)::    PROPELLER_PROFILE_foo.o := y - For enabling all files in one directory::    PROPELLER_PROFILE := y - For disabling one file::    PROPELLER_PROFILE_foo.o := n - For disabling all files in one directory::    PROPELLER__PROFILE := n  Workflow======== Here is an example workflow for building an AutoFDO+Propeller kernel: 1) Assuming an AutoFDO profile is already collected following   instructions in the AutoFDO document, build the kernel on the host   machine, with AutoFDO and Propeller build configs ::       CONFIG_AUTOFDO_CLANG=y      CONFIG_PROPELLER_CLANG=y    and ::       $ make LLVM=1 CLANG_AUTOFDO_PROFILE=<autofdo-profile-name> 2) Install the kernel on the test machine. 3) Run the load tests. The '-c' option in perf specifies the sample   event period. We suggest using a suitable prime number, like 500009,   for this purpose.    - For Intel platforms::       $ perf record -e BR_INST_RETIRED.NEAR_TAKEN:k -a -N -b -c <count> -o <perf_file> -- <loadtest>    - For AMD platforms::       $ perf record --pfm-event RETIRED_TAKEN_BRANCH_INSTRUCTIONS:k -a -N -b -c <count> -o <perf_file> -- <loadtest>    - For arm64 with SPE::     There are a few kernel features that must be enabled to collect SPE profiles on Arm.     Below is a list of the required features:       - CONFIG_ARM_SPE_PMU=y      - CONFIG_PID_IN_CONTEXTIDR=y      - kpti=off      Use the following command to generate SPE perf data file::       $ perf record -e 'arm_spe_0/branch_filter=1,load_filter=0,store_filter=0/' -a -N -c <count> --no-switch-events -o <perf_file> -- <loadtest>      Note you can repeat the above steps to collect multiple <perf_file>s. 4) (Optional) Download the raw perf file(s) to the host machine. 5) Use the generate_propeller_profiles tool (https://github.com/google/llvm-propeller) to   generate Propeller profile. ::       $ generate_propeller_profiles \             --binary=<vmlinux> --profile=<perf_file> \             --format=propeller --propeller_output_module_name \             --out=<propeller_profile_prefix>_cc_profile.txt \             --propeller_symorder=<propeller_profile_prefix>_ld_profile.txt    "<propeller_profile_prefix>" can be something like "/home/user/dir/any_string".    This command generates a pair of Propeller profiles:   "<propeller_profile_prefix>_cc_profile.txt" and   "<propeller_profile_prefix>_ld_profile.txt".    If there are more than 1 perf_file collected in the previous step,   you can create a temp list file "<perf_file_list>" with each line   containing one perf file name and run::       $ generate_propeller_profiles \             --binary=<vmlinux> --profile=@<perf_file_list> \             --format=propeller --propeller_output_module_name \             --out=<propeller_profile_prefix>_cc_profile.txt \             --propeller_symorder=<propeller_profile_prefix>_ld_profile.txt    For arm64 SPE, add the option '--profiler=perf_spe', like::       $ generate_propeller_profiles  \             --binary=<vmlinux> --profile=<perf_file> \             --profiler=perf_spe \             --format=propeller --propeller_output_module_name \             --out=<propeller_profile_prefix>_cc_profile.txt \             --propeller_symorder=<propeller_profile_prefix>_ld_profile.txt 6) Rebuild the kernel using the AutoFDO and Propeller   profiles. ::       CONFIG_AUTOFDO_CLANG=y      CONFIG_PROPELLER_CLANG=y    and ::       $ make LLVM=1 CLANG_AUTOFDO_PROFILE=<profile_file> CLANG_PROPELLER_PROFILE_PREFIX=<propeller_profile_prefix>